For CIFAR100-LT, we used ResNet-32 with a batch size of 256 on one 1080Ti GPU. The models are trained for 200 epochs with multi-step learning rate scheduler with warm-up like BBN [1]}. The learning rate is initialized as 0.2 and decayed by \(0.01\)  at epoch 120 and 160 respectively.
